Silicon Valley loves AI: Report from the US 01/18

Human observations on the Bay Area’s latest hype cycle

You don’t need to run a set of fancy new algorithms to see that artificial intelligence is one the biggest current topics. Silicon Valley and other tech hotspots keep churning out promising startups as well as wannabes that try to merely dress up their worn business models with the .ai domain.

But there are a few names around Northern California that get everybody’s attention when they unveil a new venture to propagate AI deeper and further into the mainstream.

Andrew Ng is one of them. The Chinese star computer scientist first led the Google Brain team and then ran Baidu’s ambitious AI efforts before suddenly leaving the company with a mysterious teaser that he’d return with a smaller AI outfit “to help people.” [1]

And to show he’s serious about his ambitions, Ng has also launched his own AI Fund with an initial $175 million to help launch "new businesses that use AI to improve human life.” [2]

Turns out the “people” Ng was thinking of are manufacturers. His latest venture called Landing.ai will work on bringing AI and deep learning to the factory floor to supercharge automation. The Palo Alto-based startup already has signed a few big names to work with, among them iPhone contract manufacturer Foxconn. Its mission: to improve product yield and quality control by way of visual inspection. Ng’s endeavor and name recognition will almost guarantee that what you might call Industry 5.0 gets a closer look and more early adopters.

AI pros are equally intrigued by Scott Gourley, one half of the the duo that launched the trend-spotting platform Quid back in 2006. It was far ahead of the curve by helping large corporations from Microsoft to Samsung visualize and map the global innovation landscape to discover what’s next.

The trained physicist has hung out a new shingle in SF to launch Primer.ai with $15 million of VC money. His first customers are Walmart, financial players plus various customarily tight-lipped parts of the US government, including the CIA’s venture arm In-Q-Tel. They’ve all bought into his sales pitch that AI can augment or even replace intelligence analysts by automatically digesting and summarizing massive amounts of documents in, so far, English, Chinese and Russian. Humans won’t be able to read everything that’s out there, but they sure want to read the machine-condensed digest that Gourley’s system spits out.

All told, U.S.-based AI startups bagged almost $2.9 billion in venture capital through the first three quarters of 2017, according to the scorekeepers at Crunchbase. [3] With this much funding and founding activity going on, it’s always good to check in with those experts who still have their feet firmly on the ground.

Stanford University’s AI Index provides this valuable service. It does an admirable job separating hype from reality by measuring basic research and academic publications as well as startup activity and job postings.

The assembled experts reach a sobering yet optimistic conclusion. Progress has been oversold and problems understated, a combination that can have some potentially bad consequences. The road to an artificial general intelligence (and hence the Singularity) is longer and bumpier than some AI boosters would have you believe. “We are essentially ‘flying blind’ in our conversations and decision-making related to Artificial Intelligence,” the experts warn. [4] Their thorough analysis is backed up by plenty of stats to chum your next AI discussion.

Speaking of chumming, there was blood in the water at last December’s NIPS event (short for Neural Information Processing Systems). It’s a multi-track conference around all things machine learning and computational neuroscience. (For a fascinating, 43-page-long summary of the conference highlights written by Brown University’s David Abel [5], head to his NIPS notes.)

One thing you won’t find in his AI digest is the change of pace. What used to be a decidedly quiet and nerdy gathering this time was a feeding frenzy. The event in Long Beach south of LA crawled with reporters from mainstream media and, even more importantly, with representatives from venture firms, banks and hedge funds.

They were all hunting for future AI talent. Since Wall Street will one day soon be run by algos, and that seems to be the accepted wisdom, it can’t hurt to scoop up the people who’ll build them.

If the world of AI needed a new year’s resolution, it should be this: keep things a bit on the lighter side instead of always droning on about the serious stuff like mass-scale facial recognition, automated skin cancer diagnosis or autonomous vehicles that can read a human’s intention.

How about something entertaining? Well, it’s being cued up right now. Researchers and tinkerers have produced two examples which show that computers are getting better at our own game of creativity.

A startup CTO and a music producer have developed a machine learning system that composed and then played an entire black metal album entitled “Coditany of Time.” The resulting five tracks by Dadabots are free to stream and download on music platform Bandcamp. [6]

Trained on a real-world metal band, the algorithms ingested the band’s music snippet by snippet and then tried to imitate each packet’s wavelengths. The dark robo-shredding actually sounds pretty convincing, if – and that’s a big if – you’re into this type of music.

With AI writing sports updates, news and other trivial nonfiction, how about commissioning an algo to write about a genre that’s arguably closest to its synthetic heart: science fiction. That’s what Adam Hammond [7] and Julian Brooke [8], two Canadian researchers, set out to do with their program SciFiQ. Writer Stephen Marche [9] gave them a list of his favorite sci-fi works and they came up with 14 rules to craft a short story [10] in silico.

The ultimate test came when tech magazine Wired submitted the piece to two human editors and asked them for their opinion about this unnamed newcomer’s potential. The feedback wasn’t enthusiastic but definitely cautiously encouraging, pointing out where the algo had room for improvement. The fiction editor of the New Yorker took the bait and opined that “perhaps this is all setup for a longer story or a novel?” [11]

No wonder global consultancy McKinsey has teamed up with the MIT Lab for Social Machines and published a timely report why the future belongs to “machines as co-creators.” [12]

Based in San Francisco, Steffan Heuer has been covering technology and innovation in the Bay Area for 20 years. His work has appeared in The Economist, the German business magazine brand eins, the MIT Tech Review and other international publications.